In [1]:
%matplotlib inline
Import custom scripts¶
In [2]:
path_scripts = '/mnt/kauffman/joosts/projects/STRT_epidermis/scripts'
In [3]:
import sys
sys.path.append(path_scripts)
In [4]:
from EPI_misc_scripts_v1_1 import *
from EPI_affinity_propagation_v1_0 import *
from EPI_neg_binom_regression_v1_1 import *
from EPI_pseudotemporal_ordering_v1_0 import *
from EPI_gene_neighbor_network_v1_0 import *
In [5]:
import matplotlib as mpl
Initialize engines¶
In [6]:
from ipyparallel import Client
In [7]:
c = Client(profile='default')
In [8]:
dview = c[:]
In [9]:
dview.execute('import sys')
dview.execute('sys.path.append("/mnt/kauffman/joosts/projects/STRT_epidermis/scripts")')
dview.execute('from EPI_misc_scripts_v1_1 import *')
dview.execute('from EPI_affinity_propagation_v1_0 import *')
dview.execute('from EPI_neg_binom_regression_v1_1 import *')
dview.execute('from EPI_pseudotemporal_ordering_v1_0 import *')
dview.execute('from EPI_gene_neighbor_network_v1_0 import *')
Out[9]:
Import Data¶
In [10]:
exp_id = '201509151726'
path_input = '/mnt/kauffman/joosts/projects/STRT_epidermis/data_input/v1.8'
path_output = '/mnt/kauffman/joosts/projects/STRT_epidermis/data_output/v1.8'
path_figures = '/mnt/kauffman/joosts/projects/STRT_epidermis/figures/v1.8'
In [11]:
seq = loadData_v1(path_input, exp_id, 'seq', 'DataFrame')
meta = loadData_v1(path_input, exp_id, 'meta', 'DataFrame')
In [12]:
s_groups_1st = loadData_v1(path_output, exp_id, 's_groups_1st', 'Series')
g_groups_1st = loadData_v1(path_output, exp_id, 'g_groups_1st', 'Series')
In [13]:
s_groups_2nd = loadData_v1(path_output, exp_id, 's_groups_2nd', 'Series')
In [14]:
NBR_2nd_summary = loadData_from_pickle_v1(path_output, exp_id,'NBR_2nd_summary')
NBR_2nd_bin_zero = loadData_from_pickle_v1(path_output, exp_id,'NBR_2nd_bin_zero')
NBR_2nd_size_zero = loadData_from_pickle_v1(path_output, exp_id,'NBR_2nd_size_zero')
NBR_2nd_bin_bl = loadData_from_pickle_v1(path_output, exp_id,'NBR_2nd_bin_bl')
NBR_2nd_size_bl = loadData_from_pickle_v1(path_output, exp_id,'NBR_2nd_size_bl')
Colormaps¶
In [15]:
cmap_2nd = {0:'#33a02c',
1:'#b2df8a',
2:'#00FF00',
3:'#FFE000',
4:'#FF9900',
5:'#FF3300',
6:'#CC0000',
7:'#CC0066',
8:'#FF99CC',
9:'#FFCCCC',
10:'#D2C5E1',
11:'#A68BC2',
12:'#6a3d9a',
13:'#2A183E',
14:'#000066',
15:'#0000FF',
16:'#33CCFF',
17:'#99CCFF',
18:'#666699',
19:'#000066',
20:'#33CCCC',
21:'#00FFFF',
22:'#006666',
23:'#FF99CC',
24:'#660033'}
In [16]:
markers_2nd = {0: 'o',
1: 'o',
2: 'o',
3:'s',
4:'s',
5:'s',
6:'s',
7:'^',
8:'^',
9:'^',
10:'^',
11:'^',
12:'^',
13:'^',
14:'s',
15:'D',
16:'D',
17:'D',
18:'D',
19:'D',
20:'H',
21:'H',
22:'H',
23:'s',
24:'s'}
In [17]:
markers_2nd_size = {0:750,
1:750,
2:750,
3:750,
4:750,
5:750,
6:750,
7:750,
8:750,
9:750,
10:750,
11:750,
12:750,
13:750,
14:750,
15:500,
16:500,
17:500,
18:500,
19:500,
20:750,
21:750,
22:750,
23:750,
24:750}
In [18]:
nmap_2nd_short = {0:'IFE B I',
1:'IFE B II',
2:'INFU B',
3:'IFE D I',
4:'IFE D II',
5:'IFE K I',
6:'IFE K II',
7:'uHF I',
8:'uHF II',
9:'uHF III',
10:'uHF IV',
11:'uHF V',
12:'uHF VI',
13:'uHF VII',
14:'SG',
15:'OB I',
16:'OB II',
17:'OB III',
18:'OB IV',
19:'OB V',
20:'IB I',
21:'IB II',
22:'IB III',
23:'TC',
24:'LH'}
Functional gene expression¶
In [19]:
NBR_2nd_size_zero[NBR_2nd_size_zero=='n.s'] = 0
NBR_2nd_size_bl[NBR_2nd_size_bl=='n.s'] = 0
Wnt pathway¶
In [20]:
Wnt = ['Dkk1',
'Dkk3',
'Porcn',
'Sfrp1',
'Sfrp2',
'Sfrp4',
'Wif1',
'Wnt1',
'Wnt2',
'Wnt2b',
'Wnt3',
'Wnt3a',
'Wnt4',
'Wnt5a',
'Wnt5b',
'Wnt6',
'Wnt7a',
'Wnt7b',
'Wnt8a',
'Wnt8b',
'Wnt9a',
'Wnt10a',
'Wnt11',
'Wnt16',
'Frzb',
'Fzd1',
'Fzd2',
'Fzd3',
'Fzd4',
'Fzd5',
'Fzd6',
'Fzd7',
'Fzd8',
'Fzd9',
'Kremen1',
'Lrp5',
'Lrp6',
'Lgr4',
'Lgr5',
'Lgr6',
'Aes',
'Apc',
'Axin1',
'Axin2',
'Bcl9',
'Btrc',
'Ccnd1',
'Csnk1a1',
'Csnk2a1',
'Ctbp1',
'Ctnnb1',
'Ctnnbip1',
'Daam1',
'Dixdc1',
'Dvl1',
'Dvl2',
'Ep300',
'Fbxw11',
'Frat1',
'Gsk3b',
'Lef1',
'Mapk8',
'Nfatc1',
'Nkd1',
'Nlk',
'Prickle1',
'Pygo1',
'Rhoa',
'Rhou',
'Ruvbl1',
'Tcf7',
'Tcf7l1'
'Tle1'
'Vangl2']
In [120]:
#VERSION A
#define parameters
data = NBR_2nd_size_zero.swaplevel(0,1).ix['median']
genes = Wnt
groups = data.columns[:-1]
cmap_groups = cmap_2nd
nmap_groups = nmap_2nd_short
markers_groups = markers_2nd
#define gene list
genes = data.ix[genes, groups].max(axis = 1)[data.ix[genes, groups].max(axis = 1) > 0].index
#initialize figure
height = 0.5 * len(genes) + 3
width = 0.6 * len(groups) + 1
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize GridSpec
gs = plt.GridSpec(len(genes) + 1,
len(groups) + 1,
hspace=0.0,
wspace = 0.0,
height_ratios = [3] + [0.5] * len(genes),
width_ratios = [1] + [0.5] * len(groups))
#define columns labels
for col, gr in enumerate(groups):
ax = plt.subplot(gs[0,col+1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
if gr == 'Baseline':
ax.text(0.55, 0.1, 'Baseline', family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
else:
ax.scatter(0.5,0.1,color=cmap_groups[int(gr)],marker = markers_groups[int(gr)],s = 250)
ax.text(0.55, 0.25, nmap_groups[int(gr)], family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
if col % 2 == 0:
ax.axvspan(0,1, color = '#E6E7E8', zorder = 0)
clean_axis(ax)
#define and plot rows
for ix, g in enumerate(genes):
cmax = np.log10(10 + 1)
cmap = plt.cm.RdYlGn_r
#define label
ax = plt.subplot(gs[ix+1,0])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.75, 0.5, g, family = 'Liberation Sans', fontsize = 30, va = 'center', ha = 'right')
clean_axis(ax)
#define plot
ax = plt.subplot(gs[ix+1,1:])
ax.set_xlim(0,len(groups))
ax.set_ylim(0,1)
remove_ticks(ax)
#plot data
for col, gr in enumerate(groups):
data_tmp = np.log10(data.ix[g, gr] + data.ix[g, 'Baseline'] + 1)
if data_tmp == 0:
color = 'white'
else:
color = cmap(data_tmp/cmax)
ax.axvspan(col, col + 1, color = color)
ax.axvline(col + 1, linewidth = 0.5, color = 'black')
figname = 'v1.8_7_A_Wnt_signaling.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
In [42]:
#VERSION B
#define parameters
data = NBR_2nd_size_zero.swaplevel(0,1).ix['median']
data_bl = NBR_2nd_bin_bl
genes = Wnt
groups = data.columns[:-1]
cmap_groups = cmap_2nd
nmap_groups = nmap_2nd_short
markers_groups = markers_2nd
#define gene list
genes = data.ix[genes, groups].max(axis = 1)[data.ix[genes, groups].max(axis = 1) > 0].index
#initialize figure
height = 0.5 * len(genes) + 3
width = 0.6 * len(groups) + 1
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize GridSpec
gs = plt.GridSpec(len(genes) + 1,
len(groups) + 1,
hspace=0.0,
wspace = 0.0,
height_ratios = [3] + [0.5] * len(genes),
width_ratios = [1] + [0.5] * len(groups))
#define columns labels
for col, gr in enumerate(groups):
ax = plt.subplot(gs[0,col+1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
if gr == 'Baseline':
ax.text(0.55, 0.1, 'Baseline', family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
else:
ax.scatter(0.5,0.1,color=cmap_groups[int(gr)],marker = markers_groups[int(gr)],s = 250)
ax.text(0.55, 0.25, nmap_groups[int(gr)], family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
if col % 2 == 0:
ax.axvspan(0,1, color = '#E6E7E8', zorder = 0)
clean_axis(ax)
#define and plot rows
for ix, g in enumerate(genes):
cmax = np.log10(10 + 1)
cmap = plt.cm.Greys
#define label
ax = plt.subplot(gs[ix+1,0])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.75, 0.5, g, family = 'Liberation Sans', fontsize = 30, va = 'center', ha = 'right')
clean_axis(ax)
#define plot
ax = plt.subplot(gs[ix+1,1:])
ax.set_xlim(0,len(groups))
ax.set_ylim(0,1)
remove_ticks(ax)
#plot data
for col, gr in enumerate(groups):
data_tmp = np.log10(data.ix[g, gr] + data.ix[g, 'Baseline'] + 1)
if data_tmp == 0:
color = 'white'
else:
color = cmap(data_tmp/cmax)
ax.axvspan(col, col + 1, color = color)
if data_bl.ix[g, gr] == 1:
ax.axvspan(col, col + 1, color = 'r', alpha = 0.5)
ax.axvline(col + 1, linewidth = 0.5, color = 'black')
"""
figname = 'v1.8_7_A1_Wnt_signaling.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
"""
Out[42]:
Transcription factors¶
In [43]:
TF_mm9 = open('%s/TF_mm9.txt' % path_input,'r').read().split()
TF_mm9.sort()
In [60]:
#VERSION A
#define parameters
data = NBR_2nd_size_zero.swaplevel(0,1).ix['median']
genes = TF_mm9
groups = data.columns[:-1]
cmap_groups = cmap_2nd
nmap_groups = nmap_2nd_short
markers_groups = markers_2nd
#define gene list
genes = data.ix[genes, groups].max(axis = 1)[data.ix[genes, groups].max(axis = 1) > 0].index
#initialize figure
height = 0.5 * len(genes) + 3
width = 0.6 * len(groups) + 1
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize GridSpec
gs = plt.GridSpec(len(genes) + 1,
len(groups) + 1,
hspace=0.0,
wspace = 0.0,
height_ratios = [3] + [0.5] * len(genes),
width_ratios = [1] + [0.5] * len(groups))
#define columns labels
for col, gr in enumerate(groups):
ax = plt.subplot(gs[0,col+1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
if gr == 'Baseline':
ax.text(0.55, 0.1, 'Baseline', family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
else:
ax.scatter(0.5,0.1,color=cmap_groups[int(gr)],marker = markers_groups[int(gr)],s = 250)
ax.text(0.55, 0.25, nmap_groups[int(gr)], family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
if col % 2 == 0:
ax.axvspan(0,1, color = '#E6E7E8', zorder = 0)
clean_axis(ax)
#define and plot rows
for ix, g in enumerate(genes):
cmax = np.log10(10 + 1)
cmap = plt.cm.RdYlGn_r
#define label
ax = plt.subplot(gs[ix+1,0])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.75, 0.5, g, family = 'Liberation Sans', fontsize = 30, va = 'center', ha = 'right')
clean_axis(ax)
#define plot
ax = plt.subplot(gs[ix+1,1:])
ax.set_xlim(0,len(groups))
ax.set_ylim(0,1)
remove_ticks(ax)
#plot data
for col, gr in enumerate(groups):
data_tmp = np.log10(data.ix[g, gr] + data.ix[g, 'Baseline'] + 1)
if data_tmp == 0:
color = 'white'
else:
color = cmap(data_tmp/cmax)
ax.axvspan(col, col + 1, color = color)
ax.axvline(col + 1, linewidth = 0.5, color = 'black')
"""
figname = 'v1.7b_S7_Transcription_factors.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
"""
Out[60]:
Hedgehog¶
In [48]:
Hh = ['Dhh',
'Hhat',
'Hhip',
'Ihh',
'Shh',
'Disp1',
'Disp2',
'Boc',
'Cdon',
'Gas1',
'Lrp2',
'Ptch1',
'Ptch2',
'Ptchd2',
'Ptchd3',
'Rab23',
'Smo',
'Btrc',
'Csnk1a1',
'Csnk1e',
'Fbxw11',
'Fkbp8',
'Gli1',
'Gli2',
'Gli3',
'Otx2'
'Prkaca',
'Prkacb',
'Stk36',
'Shox2'
'Sufu',
'Zic1',
'Zic2']
In [122]:
#VERSION A
#define parameters
data = NBR_2nd_size_zero.swaplevel(0,1).ix['median']
genes = Hh
groups = data.columns[:-1]
cmap_groups = cmap_2nd
nmap_groups = nmap_2nd_short
markers_groups = markers_2nd
#define gene list
genes = data.ix[genes, groups].max(axis = 1)[data.ix[genes, groups].max(axis = 1) > 0].index
#initialize figure
height = 0.5 * len(genes) + 3
width = 0.6 * len(groups) + 1
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize GridSpec
gs = plt.GridSpec(len(genes) + 1,
len(groups) + 1,
hspace=0.0,
wspace = 0.0,
height_ratios = [3] + [0.5] * len(genes),
width_ratios = [1] + [0.5] * len(groups))
#define columns labels
for col, gr in enumerate(groups):
ax = plt.subplot(gs[0,col+1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
if gr == 'Baseline':
ax.text(0.55, 0.1, 'Baseline', family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
else:
ax.scatter(0.5,0.1,color=cmap_groups[int(gr)],marker = markers_groups[int(gr)],s = 250)
ax.text(0.55, 0.25, nmap_groups[int(gr)], family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
if col % 2 == 0:
ax.axvspan(0,1, color = '#E6E7E8', zorder = 0)
clean_axis(ax)
#define and plot rows
for ix, g in enumerate(genes):
cmax = np.log10(10 + 1)
cmap = plt.cm.RdYlGn_r
#define label
ax = plt.subplot(gs[ix+1,0])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.75, 0.5, g, family = 'Liberation Sans', fontsize = 30, va = 'center', ha = 'right')
clean_axis(ax)
#define plot
ax = plt.subplot(gs[ix+1,1:])
ax.set_xlim(0,len(groups))
ax.set_ylim(0,1)
remove_ticks(ax)
#plot data
for col, gr in enumerate(groups):
data_tmp = np.log10(data.ix[g, gr] + data.ix[g, 'Baseline'] + 1)
if data_tmp == 0:
color = 'white'
else:
color = cmap(data_tmp/cmax)
ax.axvspan(col, col + 1, color = color)
ax.axvline(col + 1, linewidth = 0.5, color = 'black')
figname = 'v1.8_7_A_Hedgehog_signaling.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
BMP / TGF-beta pathway¶
In [50]:
Bmp = ['Bmp1',
'Bmp2',
'Bmp3',
'Bmp4',
'Bmp5',
'Bmp6',
'Bmp7',
'Gdf1',
'Gdf2',
'Gdf3',
'Gdf5',
'Gdf6',
'Gdf7',
'space',
'Amhr2',
'Bmpr1a',
'Bmpr1b',
'Bmpr2']
In [51]:
Tgfb = ['Tgfb1',
'Tgfb2',
'Tgfb3',
'space',
'Tgfbr1',
'Tgfbr2',
'Tgfbr3']
In [52]:
TgfbBmp = ['Bambi',
'Chrd',
'Dcn',
'Fst',
'Lefty1',
'Ltbp1',
'Ltbp2',
'Ltbp4',
'Nog',
'Tdgf1',
'Tgfbi',
'Tgfbrap1',
'Thbs1',
'Crebbp',
'Dlx2',
'Ep300',
'Fos',
'Gsc',
'Id1',
'Jun',
'Junb',
'Myc',
'Runx1',
'Smad1',
'Smad2',
'Smad3',
'Smad4',
'Smad5',
'Smad6',
'Smad7',
'Sox4',
'Stat1',
'Tgfb1i1',
'Tsc22d1']
In [123]:
#VERSION A
#define parameters
data = NBR_2nd_size_zero.swaplevel(0,1).ix['median']
genes = Bmp
groups = data.columns[:-1]
cmap_groups = cmap_2nd
nmap_groups = nmap_2nd_short
markers_groups = markers_2nd
#define gene list
genes = data.ix[genes, groups].max(axis = 1)[data.ix[genes, groups].max(axis = 1) > 0].index
#initialize figure
height = 0.5 * len(genes) + 3
width = 0.6 * len(groups) + 1
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize GridSpec
gs = plt.GridSpec(len(genes) + 1,
len(groups) + 1,
hspace=0.0,
wspace = 0.0,
height_ratios = [3] + [0.5] * len(genes),
width_ratios = [1] + [0.5] * len(groups))
#define columns labels
for col, gr in enumerate(groups):
ax = plt.subplot(gs[0,col+1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
if gr == 'Baseline':
ax.text(0.55, 0.1, 'Baseline', family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
else:
ax.scatter(0.5,0.1,color=cmap_groups[int(gr)],marker = markers_groups[int(gr)],s = 250)
ax.text(0.55, 0.25, nmap_groups[int(gr)], family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
if col % 2 == 0:
ax.axvspan(0,1, color = '#E6E7E8', zorder = 0)
clean_axis(ax)
#define and plot rows
for ix, g in enumerate(genes):
cmax = np.log10(10 + 1)
cmap = plt.cm.RdYlGn_r
#define label
ax = plt.subplot(gs[ix+1,0])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.75, 0.5, g, family = 'Liberation Sans', fontsize = 30, va = 'center', ha = 'right')
clean_axis(ax)
#define plot
ax = plt.subplot(gs[ix+1,1:])
ax.set_xlim(0,len(groups))
ax.set_ylim(0,1)
remove_ticks(ax)
#plot data
for col, gr in enumerate(groups):
data_tmp = np.log10(data.ix[g, gr] + data.ix[g, 'Baseline'] + 1)
if data_tmp == 0:
color = 'white'
else:
color = cmap(data_tmp/cmax)
ax.axvspan(col, col + 1, color = color)
ax.axvline(col + 1, linewidth = 0.5, color = 'black')
figname = 'v1.8_7_A_Bmp_signaling.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
In [124]:
#VERSION A
#define parameters
data = NBR_2nd_size_zero.swaplevel(0,1).ix['median']
genes = Tgfb
groups = data.columns[:-1]
cmap_groups = cmap_2nd
nmap_groups = nmap_2nd_short
markers_groups = markers_2nd
#define gene list
genes = data.ix[genes, groups].max(axis = 1)[data.ix[genes, groups].max(axis = 1) > 0].index
#initialize figure
height = 0.5 * len(genes) + 3
width = 0.6 * len(groups) + 1
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize GridSpec
gs = plt.GridSpec(len(genes) + 1,
len(groups) + 1,
hspace=0.0,
wspace = 0.0,
height_ratios = [3] + [0.5] * len(genes),
width_ratios = [1] + [0.5] * len(groups))
#define columns labels
for col, gr in enumerate(groups):
ax = plt.subplot(gs[0,col+1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
if gr == 'Baseline':
ax.text(0.55, 0.1, 'Baseline', family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
else:
ax.scatter(0.5,0.1,color=cmap_groups[int(gr)],marker = markers_groups[int(gr)],s = 250)
ax.text(0.55, 0.25, nmap_groups[int(gr)], family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
if col % 2 == 0:
ax.axvspan(0,1, color = '#E6E7E8', zorder = 0)
clean_axis(ax)
#define and plot rows
for ix, g in enumerate(genes):
cmax = np.log10(10 + 1)
cmap = plt.cm.RdYlGn_r
#define label
ax = plt.subplot(gs[ix+1,0])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.75, 0.5, g, family = 'Liberation Sans', fontsize = 30, va = 'center', ha = 'right')
clean_axis(ax)
#define plot
ax = plt.subplot(gs[ix+1,1:])
ax.set_xlim(0,len(groups))
ax.set_ylim(0,1)
remove_ticks(ax)
#plot data
for col, gr in enumerate(groups):
data_tmp = np.log10(data.ix[g, gr] + data.ix[g, 'Baseline'] + 1)
if data_tmp == 0:
color = 'white'
else:
color = cmap(data_tmp/cmax)
ax.axvspan(col, col + 1, color = color)
ax.axvline(col + 1, linewidth = 0.5, color = 'black')
figname = 'v1.8_7_A_Tgfb_signaling.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
In [141]:
#VERSION A
#define parameters
data = NBR_2nd_size_zero.swaplevel(0,1).ix['median']
genes = TgfbBmp
groups = data.columns[:-1]
cmap_groups = cmap_2nd
nmap_groups = nmap_2nd_short
markers_groups = markers_2nd
#define gene list
genes = data.ix[genes, groups].max(axis = 1)[data.ix[genes, groups].max(axis = 1) > 0].index
#initialize figure
height = 0.5 * len(genes) + 3
width = 0.6 * len(groups) + 1
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize GridSpec
gs = plt.GridSpec(len(genes) + 1,
len(groups) + 1,
hspace=0.0,
wspace = 0.0,
height_ratios = [3] + [0.5] * len(genes),
width_ratios = [1] + [0.5] * len(groups))
#define columns labels
for col, gr in enumerate(groups):
ax = plt.subplot(gs[0,col+1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
if gr == 'Baseline':
ax.text(0.55, 0.1, 'Baseline', family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
else:
ax.scatter(0.5,0.1,color=cmap_groups[int(gr)],marker = markers_groups[int(gr)],s = 250)
ax.text(0.55, 0.25, nmap_groups[int(gr)], family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
if col % 2 == 0:
ax.axvspan(0,1, color = '#E6E7E8', zorder = 0)
clean_axis(ax)
#define and plot rows
for ix, g in enumerate(genes):
cmax = np.log10(10 + 1)
cmap = plt.cm.RdYlGn_r
#define label
ax = plt.subplot(gs[ix+1,0])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.75, 0.5, g, family = 'Liberation Sans', fontsize = 30, va = 'center', ha = 'right')
clean_axis(ax)
#define plot
ax = plt.subplot(gs[ix+1,1:])
ax.set_xlim(0,len(groups))
ax.set_ylim(0,1)
remove_ticks(ax)
#plot data
for col, gr in enumerate(groups):
data_tmp = np.log10(data.ix[g, gr] + data.ix[g, 'Baseline'] + 1)
if data_tmp == 0:
color = 'white'
else:
color = cmap(data_tmp/cmax)
ax.axvspan(col, col + 1, color = color)
ax.axvline(col + 1, linewidth = 0.5, color = 'black')
figname = 'v1.8_7_A_Tgfb_Bmp_shared.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
Notch¶
In [56]:
Notch = ['Dll1',
'Dll3',
'Dll4',
'Jag1',
'Jag2',
'Notch1',
'Notch2',
'Notch3',
'Notch4',
'Adam10',
'Adam17',
'Dtx1'
'Ep300',
'Lfng',
'Maml1',
'Maml2',
'Mfng',
'Ncstn',
'Ncor2',
'Numb',
'Psen1',
'Psen2',
'Psenen',
'Rfng',
'Rbpjl',
'Snw1']
In [142]:
#VERSION A
#define parameters
data = NBR_2nd_size_zero.swaplevel(0,1).ix['median']
genes = Notch
groups = data.columns[:-1]
cmap_groups = cmap_2nd
nmap_groups = nmap_2nd_short
markers_groups = markers_2nd
#define gene list
genes = data.ix[genes, groups].max(axis = 1)[data.ix[genes, groups].max(axis = 1) > 0].index
#initialize figure
height = 0.5 * len(genes) + 3
width = 0.6 * len(groups) + 1
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize GridSpec
gs = plt.GridSpec(len(genes) + 1,
len(groups) + 1,
hspace=0.0,
wspace = 0.0,
height_ratios = [3] + [0.5] * len(genes),
width_ratios = [1] + [0.5] * len(groups))
#define columns labels
for col, gr in enumerate(groups):
ax = plt.subplot(gs[0,col+1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
if gr == 'Baseline':
ax.text(0.55, 0.1, 'Baseline', family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
else:
ax.scatter(0.5,0.1,color=cmap_groups[int(gr)],marker = markers_groups[int(gr)],s = 250)
ax.text(0.55, 0.25, nmap_groups[int(gr)], family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
if col % 2 == 0:
ax.axvspan(0,1, color = '#E6E7E8', zorder = 0)
clean_axis(ax)
#define and plot rows
for ix, g in enumerate(genes):
cmax = np.log10(10 + 1)
cmap = plt.cm.RdYlGn_r
#define label
ax = plt.subplot(gs[ix+1,0])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.75, 0.5, g, family = 'Liberation Sans', fontsize = 30, va = 'center', ha = 'right')
clean_axis(ax)
#define plot
ax = plt.subplot(gs[ix+1,1:])
ax.set_xlim(0,len(groups))
ax.set_ylim(0,1)
remove_ticks(ax)
#plot data
for col, gr in enumerate(groups):
data_tmp = np.log10(data.ix[g, gr] + data.ix[g, 'Baseline'] + 1)
if data_tmp == 0:
color = 'white'
else:
color = cmap(data_tmp/cmax)
ax.axvspan(col, col + 1, color = color)
ax.axvline(col + 1, linewidth = 0.5, color = 'black')
figname = 'v1.8_7_A_Notch.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
NFKB¶
In [58]:
NFKB = ['Ccl2',
'Csf2',
'Fasl',
'Ifng',
'Il10',
'Il1a',
'Il1b',
'Lta',
'Tnf',
'Tnfsf10',
'Tnfsf14',
'Card10',
'Cd40',
'Cd27',
'Egfr',
'F2r',
'Il1r1',
'Ltbr',
'Nod1',
'Tlr9',
'Tnfrsf10b',
'Tnfrsf1a',
'Tnfrsf1b',
'Tlr1',
'Tlr2',
'Tlr3',
'Tlr4',
'Tlr6',
'Fadd',
'Irak1',
'Irak2',
'Irf1',
'Map3k1',
'Mapk3',
'Myd88',
'Ripk1',
'Ripk2',
'Tradd',
'Traf2',
'Traf3',
'Traf5',
'Traf6',
'Tnfaip3',
'Tollip']
In [127]:
##VERSION A
#define parameters
data = NBR_2nd_size_zero.swaplevel(0,1).ix['median']
genes = NFKB
groups = data.columns[:-1]
cmap_groups = cmap_2nd
nmap_groups = nmap_2nd_short
markers_groups = markers_2nd
#define gene list
genes = data.ix[genes, groups].max(axis = 1)[data.ix[genes, groups].max(axis = 1) > 0].index
#initialize figure
height = 0.5 * len(genes) + 3
width = 0.6 * len(groups) + 1
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize GridSpec
gs = plt.GridSpec(len(genes) + 1,
len(groups) + 1,
hspace=0.0,
wspace = 0.0,
height_ratios = [3] + [0.5] * len(genes),
width_ratios = [1] + [0.5] * len(groups))
#define columns labels
for col, gr in enumerate(groups):
ax = plt.subplot(gs[0,col+1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
if gr == 'Baseline':
ax.text(0.55, 0.1, 'Baseline', family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
else:
ax.scatter(0.5,0.1,color=cmap_groups[int(gr)],marker = markers_groups[int(gr)],s = 250)
ax.text(0.55, 0.25, nmap_groups[int(gr)], family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
if col % 2 == 0:
ax.axvspan(0,1, color = '#E6E7E8', zorder = 0)
clean_axis(ax)
#define and plot rows
for ix, g in enumerate(genes):
cmax = np.log10(10 + 1)
cmap = plt.cm.RdYlGn_r
#define label
ax = plt.subplot(gs[ix+1,0])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.75, 0.5, g, family = 'Liberation Sans', fontsize = 30, va = 'center', ha = 'right')
clean_axis(ax)
#define plot
ax = plt.subplot(gs[ix+1,1:])
ax.set_xlim(0,len(groups))
ax.set_ylim(0,1)
remove_ticks(ax)
#plot data
for col, gr in enumerate(groups):
data_tmp = np.log10(data.ix[g, gr] + data.ix[g, 'Baseline'] + 1)
if data_tmp == 0:
color = 'white'
else:
color = cmap(data_tmp/cmax)
ax.axvspan(col, col + 1, color = color)
ax.axvline(col + 1, linewidth = 0.5, color = 'black')
figname = 'v1.8_7_A_NFKB.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
Cell adhesion¶
Tight junction¶
In [67]:
TJ = ['Cldn1',
'Cldn2',
'Cldn3',
'Cldn4',
'Cldn5',
'Cldn6',
'Cldn7',
'Cldn8',
'Cldn9',
'Cldn10',
'Cldn11',
'Cldn12',
'Cldn14',
'Cldn15',
'Cldn16',
'Cldn17',
'Cldn18',
'Cldn19',
'Esam',
'F11r',
'Icam1',
'Icam2',
'Jam2',
'Jam3',
'Ocln',
'Tjp1',
'Tjp2',
'Tjp3']
In [128]:
##VERSION A
#define parameters
data = NBR_2nd_size_zero.swaplevel(0,1).ix['median']
genes = TJ
groups = data.columns[:-1]
cmap_groups = cmap_2nd
nmap_groups = nmap_2nd_short
markers_groups = markers_2nd
#define gene list
genes = data.ix[genes, groups].max(axis = 1)[data.ix[genes, groups].max(axis = 1) > 0].index
#initialize figure
height = 0.5 * len(genes) + 3
width = 0.6 * len(groups) + 1
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize GridSpec
gs = plt.GridSpec(len(genes) + 1,
len(groups) + 1,
hspace=0.0,
wspace = 0.0,
height_ratios = [3] + [0.5] * len(genes),
width_ratios = [1] + [0.5] * len(groups))
#define columns labels
for col, gr in enumerate(groups):
ax = plt.subplot(gs[0,col+1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
if gr == 'Baseline':
ax.text(0.55, 0.1, 'Baseline', family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
else:
ax.scatter(0.5,0.1,color=cmap_groups[int(gr)],marker = markers_groups[int(gr)],s = 250)
ax.text(0.55, 0.25, nmap_groups[int(gr)], family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
if col % 2 == 0:
ax.axvspan(0,1, color = '#E6E7E8', zorder = 0)
clean_axis(ax)
#define and plot rows
for ix, g in enumerate(genes):
cmax = np.log10(10 + 1)
cmap = plt.cm.RdYlGn_r
#define label
ax = plt.subplot(gs[ix+1,0])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.75, 0.5, g, family = 'Liberation Sans', fontsize = 30, va = 'center', ha = 'right')
clean_axis(ax)
#define plot
ax = plt.subplot(gs[ix+1,1:])
ax.set_xlim(0,len(groups))
ax.set_ylim(0,1)
remove_ticks(ax)
#plot data
for col, gr in enumerate(groups):
data_tmp = np.log10(data.ix[g, gr] + data.ix[g, 'Baseline'] + 1)
if data_tmp == 0:
color = 'white'
else:
color = cmap(data_tmp/cmax)
ax.axvspan(col, col + 1, color = color)
ax.axvline(col + 1, linewidth = 0.5, color = 'black')
figname = 'v1.8_7_B_Tight_junctions.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
Focal adhesion¶
In [69]:
FA = ['Cav1',
'Cav2',
'Cav3',
'Itga1',
'Itga2',
'Itga3',
'Itga4',
'Itga5',
'Itga6',
'Itga7',
'Itga8',
'Itga9',
'Itgal',
'Itgam',
'Itgav',
'Itgb1',
'Itgb2',
'Itgb3',
'Itgb4',
'Itgb5',
'Itgb6']
In [129]:
##VERSION A
#define parameters
data = NBR_2nd_size_zero.swaplevel(0,1).ix['median']
genes = FA
groups = data.columns[:-1]
cmap_groups = cmap_2nd
nmap_groups = nmap_2nd_short
markers_groups = markers_2nd
#define gene list
genes = data.ix[genes, groups].max(axis = 1)[data.ix[genes, groups].max(axis = 1) > 0].index
#initialize figure
height = 0.5 * len(genes) + 3
width = 0.6 * len(groups) + 1
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize GridSpec
gs = plt.GridSpec(len(genes) + 1,
len(groups) + 1,
hspace=0.0,
wspace = 0.0,
height_ratios = [3] + [0.5] * len(genes),
width_ratios = [1] + [0.5] * len(groups))
#define columns labels
for col, gr in enumerate(groups):
ax = plt.subplot(gs[0,col+1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
if gr == 'Baseline':
ax.text(0.55, 0.1, 'Baseline', family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
else:
ax.scatter(0.5,0.1,color=cmap_groups[int(gr)],marker = markers_groups[int(gr)],s = 250)
ax.text(0.55, 0.25, nmap_groups[int(gr)], family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
if col % 2 == 0:
ax.axvspan(0,1, color = '#E6E7E8', zorder = 0)
clean_axis(ax)
#define and plot rows
for ix, g in enumerate(genes):
cmax = np.log10(10 + 1)
cmap = plt.cm.RdYlGn_r
#define label
ax = plt.subplot(gs[ix+1,0])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.75, 0.5, g, family = 'Liberation Sans', fontsize = 30, va = 'center', ha = 'right')
clean_axis(ax)
#define plot
ax = plt.subplot(gs[ix+1,1:])
ax.set_xlim(0,len(groups))
ax.set_ylim(0,1)
remove_ticks(ax)
#plot data
for col, gr in enumerate(groups):
data_tmp = np.log10(data.ix[g, gr] + data.ix[g, 'Baseline'] + 1)
if data_tmp == 0:
color = 'white'
else:
color = cmap(data_tmp/cmax)
ax.axvspan(col, col + 1, color = color)
ax.axvline(col + 1, linewidth = 0.5, color = 'black')
figname = 'v1.8_7_B_Focal_adhesion.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
Gap junctions¶
In [74]:
GJ = ['Gja1',
'Gja3',
'Gja4',
'Gja5',
'Gja8',
'Gjb1',
'Gjb2',
'Gjb3',
'Gjb4',
'Gjb5',
'Gjb6',
'Gjc2',
'Gjd2',
'Gje1']
In [130]:
##VERSION A
#define parameters
data = NBR_2nd_size_zero.swaplevel(0,1).ix['median']
genes = GJ
groups = data.columns[:-1]
cmap_groups = cmap_2nd
nmap_groups = nmap_2nd_short
markers_groups = markers_2nd
#define gene list
genes = data.ix[genes, groups].max(axis = 1)[data.ix[genes, groups].max(axis = 1) > 0].index
#initialize figure
height = 0.5 * len(genes) + 3
width = 0.6 * len(groups) + 1
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize GridSpec
gs = plt.GridSpec(len(genes) + 1,
len(groups) + 1,
hspace=0.0,
wspace = 0.0,
height_ratios = [3] + [0.5] * len(genes),
width_ratios = [1] + [0.5] * len(groups))
#define columns labels
for col, gr in enumerate(groups):
ax = plt.subplot(gs[0,col+1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
if gr == 'Baseline':
ax.text(0.55, 0.1, 'Baseline', family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
else:
ax.scatter(0.5,0.1,color=cmap_groups[int(gr)],marker = markers_groups[int(gr)],s = 250)
ax.text(0.55, 0.25, nmap_groups[int(gr)], family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
if col % 2 == 0:
ax.axvspan(0,1, color = '#E6E7E8', zorder = 0)
clean_axis(ax)
#define and plot rows
for ix, g in enumerate(genes):
cmax = np.log10(10 + 1)
cmap = plt.cm.RdYlGn_r
#define label
ax = plt.subplot(gs[ix+1,0])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.75, 0.5, g, family = 'Liberation Sans', fontsize = 30, va = 'center', ha = 'right')
clean_axis(ax)
#define plot
ax = plt.subplot(gs[ix+1,1:])
ax.set_xlim(0,len(groups))
ax.set_ylim(0,1)
remove_ticks(ax)
#plot data
for col, gr in enumerate(groups):
data_tmp = np.log10(data.ix[g, gr] + data.ix[g, 'Baseline'] + 1)
if data_tmp == 0:
color = 'white'
else:
color = cmap(data_tmp/cmax)
ax.axvspan(col, col + 1, color = color)
ax.axvline(col + 1, linewidth = 0.5, color = 'black')
figname = 'v1.8_7_B_Gap_junctions.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
Adherens junction¶
In [76]:
AJ = ['Cdh1',
'Cdh2',
'Dll1',
'Notch1',
'Notch2',
'Notch3',
'Notch4',
'Pvrl1',
'Pvrl2',
'Pvrl4']
In [131]:
##VERSION A
#define parameters
data = NBR_2nd_size_zero.swaplevel(0,1).ix['median']
genes = AJ
groups = data.columns[:-1]
cmap_groups = cmap_2nd
nmap_groups = nmap_2nd_short
markers_groups = markers_2nd
#define gene list
genes = data.ix[genes, groups].max(axis = 1)[data.ix[genes, groups].max(axis = 1) > 0].index
#initialize figure
height = 0.5 * len(genes) + 3
width = 0.6 * len(groups) + 1
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize GridSpec
gs = plt.GridSpec(len(genes) + 1,
len(groups) + 1,
hspace=0.0,
wspace = 0.0,
height_ratios = [3] + [0.5] * len(genes),
width_ratios = [1] + [0.5] * len(groups))
#define columns labels
for col, gr in enumerate(groups):
ax = plt.subplot(gs[0,col+1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
if gr == 'Baseline':
ax.text(0.55, 0.1, 'Baseline', family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
else:
ax.scatter(0.5,0.1,color=cmap_groups[int(gr)],marker = markers_groups[int(gr)],s = 250)
ax.text(0.55, 0.25, nmap_groups[int(gr)], family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
if col % 2 == 0:
ax.axvspan(0,1, color = '#E6E7E8', zorder = 0)
clean_axis(ax)
#define and plot rows
for ix, g in enumerate(genes):
cmax = np.log10(10 + 1)
cmap = plt.cm.RdYlGn_r
#define label
ax = plt.subplot(gs[ix+1,0])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.75, 0.5, g, family = 'Liberation Sans', fontsize = 30, va = 'center', ha = 'right')
clean_axis(ax)
#define plot
ax = plt.subplot(gs[ix+1,1:])
ax.set_xlim(0,len(groups))
ax.set_ylim(0,1)
remove_ticks(ax)
#plot data
for col, gr in enumerate(groups):
data_tmp = np.log10(data.ix[g, gr] + data.ix[g, 'Baseline'] + 1)
if data_tmp == 0:
color = 'white'
else:
color = cmap(data_tmp/cmax)
ax.axvspan(col, col + 1, color = color)
ax.axvline(col + 1, linewidth = 0.5, color = 'black')
figname = 'v1.8_7_B_Adherens_junctions.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
Desmosomes¶
In [78]:
Des = ['Dsc1',
'Dsc2',
'Dsc3',
'Dsg1a',
'Dsg2',
'Dsg3',
'Dsg4',
'Dsp',
'Jup']
In [132]:
##VERSION A
#define parameters
data = NBR_2nd_size_zero.swaplevel(0,1).ix['median']
genes = Des
groups = data.columns[:-1]
cmap_groups = cmap_2nd
nmap_groups = nmap_2nd_short
markers_groups = markers_2nd
#define gene list
genes = data.ix[genes, groups].max(axis = 1)[data.ix[genes, groups].max(axis = 1) > 0].index
#initialize figure
height = 0.5 * len(genes) + 3
width = 0.6 * len(groups) + 1
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize GridSpec
gs = plt.GridSpec(len(genes) + 1,
len(groups) + 1,
hspace=0.0,
wspace = 0.0,
height_ratios = [3] + [0.5] * len(genes),
width_ratios = [1] + [0.5] * len(groups))
#define columns labels
for col, gr in enumerate(groups):
ax = plt.subplot(gs[0,col+1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
if gr == 'Baseline':
ax.text(0.55, 0.1, 'Baseline', family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
else:
ax.scatter(0.5,0.1,color=cmap_groups[int(gr)],marker = markers_groups[int(gr)],s = 250)
ax.text(0.55, 0.25, nmap_groups[int(gr)], family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
if col % 2 == 0:
ax.axvspan(0,1, color = '#E6E7E8', zorder = 0)
clean_axis(ax)
#define and plot rows
for ix, g in enumerate(genes):
cmax = np.log10(10 + 1)
cmap = plt.cm.RdYlGn_r
#define label
ax = plt.subplot(gs[ix+1,0])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.75, 0.5, g, family = 'Liberation Sans', fontsize = 30, va = 'center', ha = 'right')
clean_axis(ax)
#define plot
ax = plt.subplot(gs[ix+1,1:])
ax.set_xlim(0,len(groups))
ax.set_ylim(0,1)
remove_ticks(ax)
#plot data
for col, gr in enumerate(groups):
data_tmp = np.log10(data.ix[g, gr] + data.ix[g, 'Baseline'] + 1)
if data_tmp == 0:
color = 'white'
else:
color = cmap(data_tmp/cmax)
ax.axvspan(col, col + 1, color = color)
ax.axvline(col + 1, linewidth = 0.5, color = 'black')
figname = 'v1.8_7_B_Desmosomes.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
Hemidesmosomes¶
In [80]:
Hemi = ['Dst',
'Plec']
In [133]:
##VERSION A
#define parameters
data = NBR_2nd_size_zero.swaplevel(0,1).ix['median']
genes = Hemi
groups = data.columns[:-1]
cmap_groups = cmap_2nd
nmap_groups = nmap_2nd_short
markers_groups = markers_2nd
#define gene list
genes = data.ix[genes, groups].max(axis = 1)[data.ix[genes, groups].max(axis = 1) > 0].index
#initialize figure
height = 0.5 * len(genes) + 3
width = 0.6 * len(groups) + 1
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize GridSpec
gs = plt.GridSpec(len(genes) + 1,
len(groups) + 1,
hspace=0.0,
wspace = 0.0,
height_ratios = [3] + [0.5] * len(genes),
width_ratios = [1] + [0.5] * len(groups))
#define columns labels
for col, gr in enumerate(groups):
ax = plt.subplot(gs[0,col+1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
if gr == 'Baseline':
ax.text(0.55, 0.1, 'Baseline', family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
else:
ax.scatter(0.5,0.1,color=cmap_groups[int(gr)],marker = markers_groups[int(gr)],s = 250)
ax.text(0.55, 0.25, nmap_groups[int(gr)], family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
if col % 2 == 0:
ax.axvspan(0,1, color = '#E6E7E8', zorder = 0)
clean_axis(ax)
#define and plot rows
for ix, g in enumerate(genes):
cmax = np.log10(10 + 1)
cmap = plt.cm.RdYlGn_r
#define label
ax = plt.subplot(gs[ix+1,0])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.75, 0.5, g, family = 'Liberation Sans', fontsize = 30, va = 'center', ha = 'right')
clean_axis(ax)
#define plot
ax = plt.subplot(gs[ix+1,1:])
ax.set_xlim(0,len(groups))
ax.set_ylim(0,1)
remove_ticks(ax)
#plot data
for col, gr in enumerate(groups):
data_tmp = np.log10(data.ix[g, gr] + data.ix[g, 'Baseline'] + 1)
if data_tmp == 0:
color = 'white'
else:
color = cmap(data_tmp/cmax)
ax.axvspan(col, col + 1, color = color)
ax.axvline(col + 1, linewidth = 0.5, color = 'black')
figname = 'v1.8_7_B_Hemidesmosomes.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
Extracellular matrix¶
Collagens¶
In [82]:
Collagens = ['Col1a1',
'Col1a2',
'Col2a1',
'Col3a1',
'Col4a1',
'Col4a2',
'Col4a3',
'Col4a4',
'Col4a5',
'Col4a6',
'Col5a1',
'Col5a2',
'Col5a3',
'Col6a1',
'Col6a2',
'Col6a3',
'Col6a5',
'Col6a6',
'Col8a1',
'Col8a2',
'Col9a1',
'Col9a2',
'Col9a3',
'Col10a1',
'Col11a1',
'Col11a2',
'Col15a1',
'Col17a1',
'Col18a1',
'Col20a1',
'Col24a1',
'Col27a1',
'Col28a1']
In [134]:
##VERSION A
#define parameters
data = NBR_2nd_size_zero.swaplevel(0,1).ix['median']
genes = Collagens
groups = data.columns[:-1]
cmap_groups = cmap_2nd
nmap_groups = nmap_2nd_short
markers_groups = markers_2nd
#define gene list
genes = data.ix[genes, groups].max(axis = 1)[data.ix[genes, groups].max(axis = 1) > 0].index
#initialize figure
height = 0.5 * len(genes) + 3
width = 0.6 * len(groups) + 1
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize GridSpec
gs = plt.GridSpec(len(genes) + 1,
len(groups) + 1,
hspace=0.0,
wspace = 0.0,
height_ratios = [3] + [0.5] * len(genes),
width_ratios = [1] + [0.5] * len(groups))
#define columns labels
for col, gr in enumerate(groups):
ax = plt.subplot(gs[0,col+1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
if gr == 'Baseline':
ax.text(0.55, 0.1, 'Baseline', family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
else:
ax.scatter(0.5,0.1,color=cmap_groups[int(gr)],marker = markers_groups[int(gr)],s = 250)
ax.text(0.55, 0.25, nmap_groups[int(gr)], family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
if col % 2 == 0:
ax.axvspan(0,1, color = '#E6E7E8', zorder = 0)
clean_axis(ax)
#define and plot rows
for ix, g in enumerate(genes):
cmax = np.log10(10 + 1)
cmap = plt.cm.RdYlGn_r
#define label
ax = plt.subplot(gs[ix+1,0])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.75, 0.5, g, family = 'Liberation Sans', fontsize = 30, va = 'center', ha = 'right')
clean_axis(ax)
#define plot
ax = plt.subplot(gs[ix+1,1:])
ax.set_xlim(0,len(groups))
ax.set_ylim(0,1)
remove_ticks(ax)
#plot data
for col, gr in enumerate(groups):
data_tmp = np.log10(data.ix[g, gr] + data.ix[g, 'Baseline'] + 1)
if data_tmp == 0:
color = 'white'
else:
color = cmap(data_tmp/cmax)
ax.axvspan(col, col + 1, color = color)
ax.axvline(col + 1, linewidth = 0.5, color = 'black')
figname = 'v1.8_7_C_Collagens.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
Laminins¶
In [84]:
Laminins = ['Lama1',
'Lama2',
'Lama3',
'Lama4',
'Lama5',
'Lamb1',
'Lamb2',
'Lamb3',
'Lamb4',
'Lamc1',
'Lamc2',
'Lamc3']
In [135]:
##VERSION A
#define parameters
data = NBR_2nd_size_zero.swaplevel(0,1).ix['median']
genes = Laminins
groups = data.columns[:-1]
cmap_groups = cmap_2nd
nmap_groups = nmap_2nd_short
markers_groups = markers_2nd
#define gene list
genes = data.ix[genes, groups].max(axis = 1)[data.ix[genes, groups].max(axis = 1) > 0].index
#initialize figure
height = 0.5 * len(genes) + 3
width = 0.6 * len(groups) + 1
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize GridSpec
gs = plt.GridSpec(len(genes) + 1,
len(groups) + 1,
hspace=0.0,
wspace = 0.0,
height_ratios = [3] + [0.5] * len(genes),
width_ratios = [1] + [0.5] * len(groups))
#define columns labels
for col, gr in enumerate(groups):
ax = plt.subplot(gs[0,col+1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
if gr == 'Baseline':
ax.text(0.55, 0.1, 'Baseline', family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
else:
ax.scatter(0.5,0.1,color=cmap_groups[int(gr)],marker = markers_groups[int(gr)],s = 250)
ax.text(0.55, 0.25, nmap_groups[int(gr)], family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
if col % 2 == 0:
ax.axvspan(0,1, color = '#E6E7E8', zorder = 0)
clean_axis(ax)
#define and plot rows
for ix, g in enumerate(genes):
cmax = np.log10(10 + 1)
cmap = plt.cm.RdYlGn_r
#define label
ax = plt.subplot(gs[ix+1,0])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.75, 0.5, g, family = 'Liberation Sans', fontsize = 30, va = 'center', ha = 'right')
clean_axis(ax)
#define plot
ax = plt.subplot(gs[ix+1,1:])
ax.set_xlim(0,len(groups))
ax.set_ylim(0,1)
remove_ticks(ax)
#plot data
for col, gr in enumerate(groups):
data_tmp = np.log10(data.ix[g, gr] + data.ix[g, 'Baseline'] + 1)
if data_tmp == 0:
color = 'white'
else:
color = cmap(data_tmp/cmax)
ax.axvspan(col, col + 1, color = color)
ax.axvline(col + 1, linewidth = 0.5, color = 'black')
figname = 'v1.8_7_C_Laminins.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
ECM Proteases¶
In [86]:
ECM_proteases = ['Adamts1',
'Adamts2',
'Adamts4',
'Adamts5',
'Adamts8',
'Adamts9',
'Adamts13',
'Adamts15',
'Adamts16',
'Adamts17',
'Adamts18',
'Adamts19',
'Adamts20',
'Adamtsl1',
'Adamtsl3',
'Adamtsl4',
'Adamtsl5',
'Cp',
'Mmp1a',
'Mmp2',
'Mmp3',
'Mmp7',
'Mmp8',
'Mmp9',
'Mmp10',
'Mmp11',
'Mmp12',
'Mmp13',
'Mmp14',
'Mmp15',
'Mmp16',
'Mmp17',
'Mmp20',
'Mmp23',
'Mmp24',
'Mmp25',
'Mmp27',
'Mmp28',
'Thsd4']
In [136]:
##VERSION A
#define parameters
data = NBR_2nd_size_zero.swaplevel(0,1).ix['median']
genes = ECM_proteases
groups = data.columns[:-1]
cmap_groups = cmap_2nd
nmap_groups = nmap_2nd_short
markers_groups = markers_2nd
#define gene list
genes = data.ix[genes, groups].max(axis = 1)[data.ix[genes, groups].max(axis = 1) > 0].index
#initialize figure
height = 0.5 * len(genes) + 3
width = 0.6 * len(groups) + 1
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize GridSpec
gs = plt.GridSpec(len(genes) + 1,
len(groups) + 1,
hspace=0.0,
wspace = 0.0,
height_ratios = [3] + [0.5] * len(genes),
width_ratios = [1] + [0.5] * len(groups))
#define columns labels
for col, gr in enumerate(groups):
ax = plt.subplot(gs[0,col+1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
if gr == 'Baseline':
ax.text(0.55, 0.1, 'Baseline', family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
else:
ax.scatter(0.5,0.1,color=cmap_groups[int(gr)],marker = markers_groups[int(gr)],s = 250)
ax.text(0.55, 0.25, nmap_groups[int(gr)], family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
if col % 2 == 0:
ax.axvspan(0,1, color = '#E6E7E8', zorder = 0)
clean_axis(ax)
#define and plot rows
for ix, g in enumerate(genes):
cmax = np.log10(10 + 1)
cmap = plt.cm.RdYlGn_r
#define label
ax = plt.subplot(gs[ix+1,0])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.75, 0.5, g, family = 'Liberation Sans', fontsize = 30, va = 'center', ha = 'right')
clean_axis(ax)
#define plot
ax = plt.subplot(gs[ix+1,1:])
ax.set_xlim(0,len(groups))
ax.set_ylim(0,1)
remove_ticks(ax)
#plot data
for col, gr in enumerate(groups):
data_tmp = np.log10(data.ix[g, gr] + data.ix[g, 'Baseline'] + 1)
if data_tmp == 0:
color = 'white'
else:
color = cmap(data_tmp/cmax)
ax.axvspan(col, col + 1, color = color)
ax.axvline(col + 1, linewidth = 0.5, color = 'black')
figname = 'v1.8_7_C_ECM_Proteases.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
ECM Protease inhibitors¶
In [88]:
ECM_protease_inhibitors = ['Timp1',
'Timp2',
'Timp3']
In [137]:
##VERSION A
#define parameters
data = NBR_2nd_size_zero.swaplevel(0,1).ix['median']
genes = ECM_protease_inhibitors
groups = data.columns[:-1]
cmap_groups = cmap_2nd
nmap_groups = nmap_2nd_short
markers_groups = markers_2nd
#define gene list
genes = data.ix[genes, groups].max(axis = 1)[data.ix[genes, groups].max(axis = 1) > 0].index
#initialize figure
height = 0.5 * len(genes) + 3
width = 0.6 * len(groups) + 1
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize GridSpec
gs = plt.GridSpec(len(genes) + 1,
len(groups) + 1,
hspace=0.0,
wspace = 0.0,
height_ratios = [3] + [0.5] * len(genes),
width_ratios = [1] + [0.5] * len(groups))
#define columns labels
for col, gr in enumerate(groups):
ax = plt.subplot(gs[0,col+1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
if gr == 'Baseline':
ax.text(0.55, 0.1, 'Baseline', family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
else:
ax.scatter(0.5,0.1,color=cmap_groups[int(gr)],marker = markers_groups[int(gr)],s = 250)
ax.text(0.55, 0.25, nmap_groups[int(gr)], family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
if col % 2 == 0:
ax.axvspan(0,1, color = '#E6E7E8', zorder = 0)
clean_axis(ax)
#define and plot rows
for ix, g in enumerate(genes):
cmax = np.log10(10 + 1)
cmap = plt.cm.RdYlGn_r
#define label
ax = plt.subplot(gs[ix+1,0])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.75, 0.5, g, family = 'Liberation Sans', fontsize = 30, va = 'center', ha = 'right')
clean_axis(ax)
#define plot
ax = plt.subplot(gs[ix+1,1:])
ax.set_xlim(0,len(groups))
ax.set_ylim(0,1)
remove_ticks(ax)
#plot data
for col, gr in enumerate(groups):
data_tmp = np.log10(data.ix[g, gr] + data.ix[g, 'Baseline'] + 1)
if data_tmp == 0:
color = 'white'
else:
color = cmap(data_tmp/cmax)
ax.axvspan(col, col + 1, color = color)
ax.axvline(col + 1, linewidth = 0.5, color = 'black')
figname = 'v1.8_7_C_ECM_Protease_inhibitors.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
ECM glycoproteins¶
In [90]:
ECM_glyco = ['Acan',
'Agrn',
'Ahsg',
'Bcan',
'Bmper',
'Chrd',
'Crim1',
'Edil3',
'Emilin1',
'Fbln1',
'Fbn1',
'Fbn2',
'Fcgbp',
'Fn1',
'Gp9',
'Hapln1',
'Hapln2',
'Hapln3',
'Hapln4',
'Lepre1',
'Leprel1',
'Leprel2',
'Ltbp1',
'Ltbp4',
'Mfap2',
'Mfap3',
'Mfap3l',
'Mfap5',
'Msln',
'Mslnl',
'Muc2',
'Muc5ac',
'Muc5b',
'Muc6',
'Muc19',
'Ncan',
'Nid1',
'Nid2',
'Otoa',
'Otog',
'Otogl',
'Papln',
'Sepp1',
'Sparc',
'Sparcl1',
'Strc',
'Tecta',
'Vcan',
'Vwf',
'Zan']
In [138]:
##VERSION A
#define parameters
data = NBR_2nd_size_zero.swaplevel(0,1).ix['median']
genes = ECM_glyco
groups = data.columns[:-1]
cmap_groups = cmap_2nd
nmap_groups = nmap_2nd_short
markers_groups = markers_2nd
#define gene list
genes = data.ix[genes, groups].max(axis = 1)[data.ix[genes, groups].max(axis = 1) > 0].index
#initialize figure
height = 0.5 * len(genes) + 3
width = 0.6 * len(groups) + 1
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize GridSpec
gs = plt.GridSpec(len(genes) + 1,
len(groups) + 1,
hspace=0.0,
wspace = 0.0,
height_ratios = [3] + [0.5] * len(genes),
width_ratios = [1] + [0.5] * len(groups))
#define columns labels
for col, gr in enumerate(groups):
ax = plt.subplot(gs[0,col+1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
if gr == 'Baseline':
ax.text(0.55, 0.1, 'Baseline', family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
else:
ax.scatter(0.5,0.1,color=cmap_groups[int(gr)],marker = markers_groups[int(gr)],s = 250)
ax.text(0.55, 0.25, nmap_groups[int(gr)], family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
if col % 2 == 0:
ax.axvspan(0,1, color = '#E6E7E8', zorder = 0)
clean_axis(ax)
#define and plot rows
for ix, g in enumerate(genes):
cmax = np.log10(10 + 1)
cmap = plt.cm.RdYlGn_r
#define label
ax = plt.subplot(gs[ix+1,0])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.75, 0.5, g, family = 'Liberation Sans', fontsize = 30, va = 'center', ha = 'right')
clean_axis(ax)
#define plot
ax = plt.subplot(gs[ix+1,1:])
ax.set_xlim(0,len(groups))
ax.set_ylim(0,1)
remove_ticks(ax)
#plot data
for col, gr in enumerate(groups):
data_tmp = np.log10(data.ix[g, gr] + data.ix[g, 'Baseline'] + 1)
if data_tmp == 0:
color = 'white'
else:
color = cmap(data_tmp/cmax)
ax.axvspan(col, col + 1, color = color)
ax.axvline(col + 1, linewidth = 0.5, color = 'black')
figname = 'v1.8_7_C_ECM_Glycoproteins.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
Other ECM proteins¶
In [92]:
ECM_other = ['Ambn',
'Aspn',
'Astl',
'Atrn',
'Atrnl1',
'Bglap',
'Bglap-rs1',
'Bglap2',
'Bgn',
'C1qtnf7',
'Chad',
'Cntnap4',
'Cntnap5a',
'Cntnap5b',
'Cntnap5c',
'Colec12',
'Colq',
'Ctgf',
'Cubn',
'Dcn',
'Dlk1',
'Ecm1',
'Ecm2',
'Egfl6',
'Epyc',
'Flrt1',
'Flrt2',
'Flrt3',
'Fmod',
'Gas6',
'Gm884',
'Hephl1',
'Hmcn1',
'Hspg2',
'Ibsp',
'Islr',
'Islr2',
'Kera',
'Lrrc4',
'Lrrc4b',
'Lrrc4c',
'Lrrc9',
'Lrrc15',
'Lrrc19',
'Lrrc32',
'Lrrc37a',
'Lrrc66',
'Lrriq1',
'Lrrn4',
'Lrrn4cl',
'Lrrtm1',
'Lrrtm3',
'Lrrtm4',
'Lrtm1',
'Lum',
'Mep1b',
'Megf6',
'Megf8',
'Megf9',
'Megf10',
'Megf11',
'Mep1a',
'Mfge8',
'Msr1',
'Neto1',
'Npnt',
'Nrp1',
'Nrp2',
'Nrros',
'Nrxn1',
'Nrxn2',
'Nrxn3',
'Ntn1',
'Ntn3',
'Ntn4',
'Ntn5',
'Ntng1',
'Ntng2',
'Nyx',
'Oc90',
'Ogn',
'Omd',
'Optc',
'Otol1',
'Pelp1',
'Pcolce',
'Pcolce2',
'Podn',
'Podnl1',
'Postn',
'Prelp',
'Prg2',
'Prg3',
'Rtn4r',
'Rtn4rl2',
'Scara3',
'Scara5',
'Slit1',
'Slit2',
'Slit3',
'Stab1',
'Stab2',
'Tpbgl',
'Ush2A',
'Wisp1',
'Wisp2',
'Wisp3']
In [139]:
##VERSION A
#define parameters
data = NBR_2nd_size_zero.swaplevel(0,1).ix['median']
genes = ECM_other
groups = data.columns[:-1]
cmap_groups = cmap_2nd
nmap_groups = nmap_2nd_short
markers_groups = markers_2nd
#define gene list
genes = data.ix[genes, groups].max(axis = 1)[data.ix[genes, groups].max(axis = 1) > 0].index
#initialize figure
height = 0.5 * len(genes) + 3
width = 0.6 * len(groups) + 1
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize GridSpec
gs = plt.GridSpec(len(genes) + 1,
len(groups) + 1,
hspace=0.0,
wspace = 0.0,
height_ratios = [3] + [0.5] * len(genes),
width_ratios = [1] + [0.5] * len(groups))
#define columns labels
for col, gr in enumerate(groups):
ax = plt.subplot(gs[0,col+1])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
if gr == 'Baseline':
ax.text(0.55, 0.1, 'Baseline', family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
else:
ax.scatter(0.5,0.1,color=cmap_groups[int(gr)],marker = markers_groups[int(gr)],s = 250)
ax.text(0.55, 0.25, nmap_groups[int(gr)], family = 'Liberation Sans', fontsize = 30,
va = 'bottom', ha = 'center', rotation = 'vertical')
if col % 2 == 0:
ax.axvspan(0,1, color = '#E6E7E8', zorder = 0)
clean_axis(ax)
#define and plot rows
for ix, g in enumerate(genes):
cmax = np.log10(10 + 1)
cmap = plt.cm.RdYlGn_r
#define label
ax = plt.subplot(gs[ix+1,0])
ax.set_xlim(0,1)
ax.set_ylim(0,1)
ax.text(0.75, 0.5, g, family = 'Liberation Sans', fontsize = 30, va = 'center', ha = 'right')
clean_axis(ax)
#define plot
ax = plt.subplot(gs[ix+1,1:])
ax.set_xlim(0,len(groups))
ax.set_ylim(0,1)
remove_ticks(ax)
#plot data
for col, gr in enumerate(groups):
data_tmp = np.log10(data.ix[g, gr] + data.ix[g, 'Baseline'] + 1)
if data_tmp == 0:
color = 'white'
else:
color = cmap(data_tmp/cmax)
ax.axvspan(col, col + 1, color = color)
ax.axvline(col + 1, linewidth = 0.5, color = 'black')
figname = 'v1.8_7_C_ECM_other.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
Legend¶
In [140]:
cmap = plt.cm.RdYlGn_r
cmin = np.log10(0.1 + 1)
cmax = np.log10(10 + 1)
#initialize figure
height = 1.0
width = 25
fig = plt.figure(facecolor = 'w', figsize = (width, height))
#initialize subplot
ax = plt.subplot()
ax.set_xlim(cmin, cmax)
#plot cmap
for pos in np.arange(0, cmax, 0.001):
ax.axvspan(pos, pos + 0.001, color = cmap(pos/cmax))
clean_axis(ax)
#plot ticks
ticks = [0.25, 0.5, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
ax.set_xticks([np.log10(x + 1) for x in ticks])
ax.set_xticklabels(['0.25', '0.5', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10+'],
family = 'Liberation Sans', fontsize = 35)
#plot label
ax.set_xlabel('Number of molecules additionaly expressed in group (Baseline + group-\nspecific expression) [median of posterior probability distribution]', family = 'Liberation Sans', fontsize = 40)
figname = 'v1.8_7_Legend.pdf'
plt.savefig('%s/%s' % (path_figures, figname),
format = 'pdf',
transparent = True,
bbox_inches = 'tight',
pad_inches = 0,
rasterized = True)
